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	<title>Teadmised second lab 2011 - Redigeerimiste ajalugu</title>
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	<updated>2026-10-28T15:22:24Z</updated>
	<subtitle>Selle lehekülje redigeerimiste ajalugu</subtitle>
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	<entry>
		<id>http://www.lambda.ee/w/index.php?title=Teadmised_second_lab_2011&amp;diff=8541&amp;oldid=prev</id>
		<title>Tammet – 14. märts 2011, kell 10:16</title>
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		<updated>2011-03-14T10:16:13Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;Uus lehekülg&lt;/b&gt;&lt;/p&gt;&lt;div&gt;The main goal of the second lab is to extend data obtained during the first, web-scraping lab, using rules and a reasoning engine. &lt;br /&gt;
&lt;br /&gt;
web-scrape uncertain data from the public sources using search engines and simple text analysis/statistics. &lt;br /&gt;
&lt;br /&gt;
== Conditions ==&lt;br /&gt;
&lt;br /&gt;
You can do the lab either alone or together with a fellow student. Three students per lab is not ok, though.&lt;br /&gt;
&lt;br /&gt;
Technology - language, op system etc - is completely free EXCEPT that you have to use [http://www.cs.unm.edu/~mccune/mace2/ Otter version 3.3] as a reasoning engine. &lt;br /&gt;
&lt;br /&gt;
Ideally you should create both (a) your own rules for improving data / deriving new data and (b) rules from wordnet taxonomy to obtain generalisations from derived facts.&lt;br /&gt;
&lt;br /&gt;
The lab is graded considering (see below for details):&lt;br /&gt;
&lt;br /&gt;
* your own rules: how good/sensible they are and what results you get for a selected domain of objects&lt;br /&gt;
* rules generated from the [http://wordnet.princeton.edu/ wordnet] database&lt;br /&gt;
* quality and interestingness of the overall results&lt;br /&gt;
&lt;br /&gt;
You may skip writing your own rules (a) or wordnet rules (b) but in that case the grades for the lab will be weaker.&lt;br /&gt;
&lt;br /&gt;
== What should the app do ==&lt;br /&gt;
&lt;br /&gt;
Your system should take as input data obtained during the first lab for some object (say, &amp;quot;Statue of Liberty&amp;quot; or &amp;quot;Andrus Ansip&amp;quot;) and it should derive new facts, &lt;br /&gt;
augmented with the confidence number.&lt;br /&gt;
&lt;br /&gt;
The new facts for the object have to be derived using Otter and rules of your own making.&lt;br /&gt;
&lt;br /&gt;
As a result the full app should &lt;br /&gt;
* take a phrase like &amp;quot;Statue of Liberty&amp;quot; as input&lt;br /&gt;
* scrape raw data from the web for the phrase (use the first lab you have completed)&lt;br /&gt;
* derive new data &lt;br /&gt;
* output the full set of data, including the derived and the raw data, with confidence numbers and the indicator raw/derived for each fact.&lt;br /&gt;
&lt;br /&gt;
== Subtasks of the lab ==&lt;br /&gt;
&lt;br /&gt;
The lab is essentially split into these subtasks:&lt;br /&gt;
&lt;br /&gt;
* the main task: create the ruleset suitable for your data and the reasoner&lt;br /&gt;
* format the output of your first task so that it is suitable for the reasoner: basically the correct syntax.&lt;br /&gt;
* create the input file for the reasoner: just compose it from a header, data block, rule block and a footer.&lt;br /&gt;
* run the reasoner and send output to a file.&lt;br /&gt;
* filter out the derived facts from the reasoner output.&lt;br /&gt;
* present the full resulting dataset.&lt;br /&gt;
&lt;br /&gt;
== Creating the ruleset ==&lt;br /&gt;
&lt;br /&gt;
The main task of the lab is the ruleset creation. This requires creative thinking and experimentation with the reasoner. &lt;br /&gt;
&lt;br /&gt;
Start by downloading and installing Otter [http://www.cs.unm.edu/~mccune/mace2/ Otter version 3.3] and experiment a bit. &lt;br /&gt;
&lt;br /&gt;
It is a good idea to use the [[ITV0060 lab 2 example]] for experimentation: this file contains suitable settings. &lt;br /&gt;
Use the [http://www.cs.unm.edu/~mccune/mace2/Otter33.pdf Otter manual] for additional details and settings.&lt;br /&gt;
&lt;br /&gt;
The ruleset, as said, should contain two parts:&lt;br /&gt;
&lt;br /&gt;
(a) Your own ruleset. This should either improve the confidence of already derived facts by combining them and/or derive completely new facts.&lt;br /&gt;
&lt;br /&gt;
(b) Ruleset generated from the wordnet taxonomy database. This should generate generalisations or hypernyms in the wordnet terminology, &lt;br /&gt;
see [http://wordnetweb.princeton.edu/perl/webwn?o2=&amp;amp;o0=1&amp;amp;o7=&amp;amp;o5=&amp;amp;o1=1&amp;amp;o6=&amp;amp;o4=&amp;amp;o3=&amp;amp;r=1&amp;amp;s=car&amp;amp;i=4&amp;amp;h=10001000000#c the car hypernym]. For example,&lt;br /&gt;
from the fact that X is a car you should derive that it is motor_vehicle, vehicle, physical_entity etc.&lt;/div&gt;</summary>
		<author><name>Tammet</name></author>
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